dor_id: 4133529

506.#.#.a: Público

590.#.#.d: Los artículos enviados a la revista "Geofísica Internacional", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Consejo Nacional de Ciencia y Tecnología (CONACyT); Scientific Electronic Library Online (SciELO); SCOPUS, Dialnet, Directory of Open Access Journals (DOAJ); Geobase

561.#.#.u: https://www.geofisica.unam.mx/

650.#.4.x: Físico Matemáticas y Ciencias de la Tierra

336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: http://revistagi.geofisica.unam.mx/index.php/RGI

351.#.#.b: Geofísica Internacional

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

590.#.#.c: Open Journal Systems (OJS)

270.#.#.d: MX

270.1.#.d: México

590.#.#.b: Concentrador

883.#.#.u: https://revistas.unam.mx/catalogo/

883.#.#.a: Revistas UNAM

590.#.#.a: Coordinación de Difusión Cultural

883.#.#.1: https://www.publicaciones.unam.mx/

883.#.#.q: Dirección General de Publicaciones y Fomento Editorial

850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: http://revistagi.geofisica.unam.mx/index.php/RGI/article/view/1434/1563

100.1.#.a: Leal F., Jorge A.; Ochoa G., Luis H.; Sarmiento P., Gustavo A.

524.#.#.a: Leal F., Jorge A., et al. (2022). Content of Total Organic Carbon Using Random Forest, Borehole Imaging, and Fractal Analysis: A Methodology Applied in the Cretaceous La Luna Formation, South America. Geofísica Internacional; Vol. 61 Núm. 4: Octubre 1, 2022; 301-323. Recuperado de https://repositorio.unam.mx/contenidos/4133529

245.1.0.a: Content of Total Organic Carbon Using Random Forest, Borehole Imaging, and Fractal Analysis: A Methodology Applied in the Cretaceous La Luna Formation, South America

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Geofísica, UNAM

264.#.0.c: 2022

264.#.1.c: 2022-10-01

653.#.#.a: Formación La Luna; Carbono orgánico total; Imágenes resistivas de pozo; Bosque aleatorio; Análisis fractal y yacimientos no convencionales; La Luna Formation; Total organic carbon; Borehole resistivity imaging; Random forest; Fractal analysis and unconventional reservoirs

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-ND 4.0 Internacional, https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico revistagi@igeofisica.unam.mx

884.#.#.k: http://revistagi.geofisica.unam.mx/index.php/RGI/article/view/1434

001.#.#.#: 063.oai:revistagi.geofisica.unam.mx:article/1434

041.#.7.h: spa

520.3.#.a: This research presents an alternative approach to computing the content of total organic carbon using wireline logs and machine learning techniques. Specifically, borehole resistivity imaging, its average resistivity, and gamma rays log are employed to train a regression model. The methodology was applied in La Luna Formation, which has been reported as one of the principal source rocks for Colombia and western Venezuela. This work aims to teach a machine how to recognize patterns between fractal features in borehole images and their content of total organic carbon. Implemented machine learning is based on ensemble learning techniques, in this case, an ensemble of decision trees known as random forest. The working data set totalizes 960 wireline log measurements, randomly split into 80% for training and 20% for validation. The outcome is equivalent to the curve obtained using a semi-log regression of organic carbon measured in core against density log values.The accuracy of this method is high enough to be considered during petrophysics evaluations, showing a root-mean-square error of 0.44% and Pearson’s correlation coefficient of 0.88. The methodology depends on image quality, and anomalies in these data increase the error. The generated model must be recalibrated for other formations, for horizontal and deviated wells, and when logging while drilling imaging is employed.

773.1.#.t: Geofísica Internacional; Vol. 61 Núm. 4: Octubre 1, 2022; 301-323

773.1.#.o: http://revistagi.geofisica.unam.mx/index.php/RGI

022.#.#.a: ISSN-L: 2954-436X; ISSN impreso: 0016-7169

310.#.#.a: Trimestral

300.#.#.a: Páginas: 301-323

264.#.1.b: Instituto de Geofísica, UNAM

doi: https://doi.org/10.22201/igeof.00167169p.2022.61.4.2113

handle: 1b051df3384ee193

harvesting_date: 2023-06-20 16:00:00.0

856.#.0.q: application/pdf

file_creation_date: 2022-09-26 15:59:07.0

file_modification_date: 2022-09-29 18:45:59.0

file_creator: Jorge A. Leal F.

file_name: 29cd7e01022f20d2491216210b0d12e7ecc433db2866ea9b0f4636645661a265.pdf

file_pages_number: 23

file_format_version: application/pdf; version=1.6

file_size: 1575105

245.1.0.b: Content of Total Organic Carbon Using Random Forest, Borehole Imaging, and Fractal Analysis: A Methodology Applied in the Cretaceous La Luna Formation, South America

last_modified: 2023-06-20 16:00:00

license_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.es

license_type: by-nc-nd

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